Submission¶

Put the ipynb file and html file in the github branch you created in the last assignment and submit the link to the commit in brightspace

In [1]:
from plotly.offline import init_notebook_mode
import plotly.io as pio
import plotly.express as px

init_notebook_mode(connected=True)
pio.renderers.default = "plotly_mimetype+notebook"
In [2]:
#load data
df = px.data.gapminder()
df.head()
Out[2]:
country continent year lifeExp pop gdpPercap iso_alpha iso_num
0 Afghanistan Asia 1952 28.801 8425333 779.445314 AFG 4
1 Afghanistan Asia 1957 30.332 9240934 820.853030 AFG 4
2 Afghanistan Asia 1962 31.997 10267083 853.100710 AFG 4
3 Afghanistan Asia 1967 34.020 11537966 836.197138 AFG 4
4 Afghanistan Asia 1972 36.088 13079460 739.981106 AFG 4

Question 1:¶

Recreate the barplot below that shows the population of different continents for the year 2007.

Hints:

  • Extract the 2007 year data from the dataframe. You have to process the data accordingly
  • use plotly bar
  • Add different colors for different continents
  • Sort the order of the continent for the visualisation. Use axis layout setting
  • Add text to each bar that represents the population
In [3]:
# YOUR CODE HERE
df_2007 = df[df['year'] == 2007]
df_total_pop = df_2007.groupby('continent')['pop'].sum().reset_index()

fig = px.bar(
    df_total_pop, y='continent', x='pop', 
    color = 'continent'  
)

fig.show()

Question 2:¶

Sort the order of the continent for the visualisation

Hint: Use axis layout setting

In [5]:
# YOUR CODE HERE
df_2007 = df[df['year'] == 2007]
df_total_pop = df_2007.groupby('continent')['pop'].sum().reset_index()

fig = px.bar(
    df_total_pop, y='continent', x='pop', 
    color = 'continent'  
)

fig.update_yaxes(categoryorder='total ascending')

fig.show()

Question 3:¶

Add text to each bar that represents the population

In [11]:
# YOUR CODE HERE
df_2007 = df[df['year'] == 2007]
df_total_pop = df_2007.groupby('continent')['pop'].sum().reset_index()

fig = px.bar(
    df_total_pop, y='continent', x='pop', 
    text='pop', color = 'continent'  
)

fig.update_yaxes(categoryorder='total ascending')
fig.update_traces(
     textposition='outside',
     texttemplate='%{text:,.2s}'
)

fig.show()

Question 4:¶

Thus far we looked at data from one year (2007). Lets create an animation to see the population growth of the continents through the years

In [23]:
# YOUR CODE HERE
df_total_pop = df.groupby(['continent', 'year'])['pop'].sum().reset_index()

fig = px.bar(
    df_total_pop, 
    y='continent', 
    x='pop', 
    color='continent',  
    animation_frame='year',  
    range_x=[0, 4000000000],   
    title="Population Growth of Continents Over Time"
)

fig.update_layout(
    yaxis_title="Continent",
    xaxis_title="Pop",
    title="Population Growth of Continents",
    showlegend=False
)

fig.update_yaxes(categoryorder='total ascending')

fig.layout.updatemenus[0].buttons[0].args[1]['frame']['duration'] = 500  
fig.layout.updatemenus[0].buttons[0].args[1]['transition']['duration'] = 500  

fig.show()

Question 5:¶

Instead of the continents, lets look at individual countries. Create an animation that shows the population growth of the countries through the years

In [24]:
# YOUR CODE HERE
df_total_pop = df.groupby(['country', 'year'])['pop'].sum().reset_index()

fig = px.bar(
    df_total_pop, 
    y='country', 
    x='pop', 
    color='country',  
    animation_frame='year',  
    range_x=[0, 1500000000],    
    title="Population Growth of Countries Over Time"
)

fig.update_layout(
    yaxis_title="Country",
    xaxis_title="Pop",
    title="Population Growth of Countries",
    showlegend=False
)

fig.update_yaxes(categoryorder='total ascending')

fig.show()

Question 6:¶

Clean up the country animation. Set the height size of the figure to 1000 to have a better view of the animation

In [29]:
# YOUR CODE HERE
df_total_pop = df.groupby(['country', 'year'])['pop'].sum().reset_index()

fig = px.bar(
    df_total_pop, 
    y='country', 
    x='pop', 
    color='country',  
    animation_frame='year',  
    range_x=[0, 1500000000],   
    title="Population Growth of Countries Over Time"
)

fig.update_layout(
    yaxis_title="Country",
    xaxis_title="Pop",
    title="Population Growth of Countries",
    showlegend=False, 
    height=1000
)

fig.update_yaxes(categoryorder='total ascending')

fig.show()

Question 7:¶

Show only the top 10 countries in the animation

Hint: Use the axis limit to set this.

In [35]:
# YOUR CODE HERE
df_total_pop = df.groupby(['country', 'year'])['pop'].sum().reset_index()

top_countries = df_total_pop.groupby('country')['pop'].sum().nlargest(10).index

df_top_countries = df_total_pop[df_total_pop['country'].isin(top_countries)]

max_population = df_top_countries['pop'].max()

fig = px.bar(
    df_top_countries, 
    y='country', 
    x='pop', 
    color='country',  
    animation_frame='year',    
    title="Population Growth of Top 10 Countries Over Time"
)

fig.update_layout(
    xaxis=dict(range=[0, max_population * 1.1]), 
    yaxis_title="Country",
    xaxis_title="Pop",
    title="Population Growth of Countries",
    showlegend=False, 
    height=400
)

fig.update_yaxes(categoryorder='total ascending')

fig.show()
In [ ]: